Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Adaptive Middleware for Message Queuing Systems

  • Christophe TatonEmail author
  • Noël de Palma
  • Sara Bouchenak
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_1540


Adaptive message-oriented middleware; Autonomous message-oriented middleware; Autonomous message queuing systems


Distributed database systems are usually built on top of middleware solutions, such as message queuing systems. Adaptive message queuing systems are able to improve the performance of such a middleware through load balancing and queue provisioning.

Historical Background

The use of message oriented middlewares (MOMs) in the context of the Internet has evidenced a need for highly scalable and highly available MOM. A very promising approach to the above issue is to implement performance management as an autonomic software. The main advantages of this approach are: (i) Providing a high-level support for deploying and configuring applications reduces errors and administrator’s efforts. (ii) Autonomic management allows the required reconfigurations to be performed without human intervention, thus improving the system reactivity and saving administrator’s time....

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Recommended Reading

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    Aron M, Druschel P, Zwaenepoel W. Cluster reserves: a mechanism for resource management in cluster-based network servers. In: Proceedings of the 2000 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems; 2000. p. 90–101.Google Scholar
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    Menth M, Henjes R. Analysis of the message waiting time for the fioranoMQ JMS server. In: Proceedings of the 23rd International Conference on Distributed Computing Systems; 2006. p. 1.Google Scholar
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    Shen K, Tang H, Yang T, Chu L. Integrated resource management for cluster-based internet services. In: Proceedings of the 5th USENIX Symposium on Operating System Design and Implementation; 2002.Google Scholar
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    Urgaonkar B, Shenoy P. Sharc: managing CPU and network bandwidth in shared clusters. IEEE Trans Parall Distrib Syst. 2004;15(1):2–17.CrossRefGoogle Scholar
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    Zhu H, Ti H, Yang Y. Demand-driven service differentiation in cluster-based network servers. In: Proceedings of the 20th Annual Joint Conference of the IEEE Computer and Communications Societies; 2001. p. 679–88.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Christophe Taton
    • 1
    Email author
  • Noël de Palma
    • 1
  • Sara Bouchenak
    • 2
  1. 1.INPG – INRIAGrenobleFrance
  2. 2.University of Grenoble I – INRIAGrenobleFrance

Section editors and affiliations

  • Cristiana Amza
    • 1
  1. 1.Dept. of Elec. and Comp. Eng.Univ. of TorontoTorontoCanada